Saving weights and logs of epoch 100

flax_model.msgpack

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1672bb6f04da617591d445601d1fa273deedb722149ff324265c8f1ee4ace542
+oid sha256:04bc3c643aa06fce3f104300b758f4421eeac2a267542a29923c58ca922ef108
 size 1200715307

run_translation_t5_flax.py

@@ -431,13 +431,13 @@ def main():
     # Setting padding="max_length" as we need fixed length inputs for jitted functions
     def preprocess_function(examples):
         #Make it two way
-        #inputs = examples[text_column]
-        inputs = examples[text_column][0:int(len(examples)/2)]
-        inputs.extend(examples[summary_column][int(len(examples)/2):])
+        inputs = examples[text_column]
+        #inputs = examples[text_column][0:int(len(examples)/2)]
+        #inputs.extend(examples[summary_column][int(len(examples)/2):])
 
-        #targets = examples[summary_column]
-        targets = examples[summary_column][0:int(len(examples)/2)]
-        targets.extend(examples[text_column][int(len(examples)/2):])
+        targets = examples[summary_column]
+        #targets = examples[summary_column][0:int(len(examples)/2)]
+        #targets.extend(examples[text_column][int(len(examples)/2):])
 
         inputs = [prefix + inp for inp in inputs]
         model_inputs = tokenizer(